Bank Marketing Dataset

Bank Marketing Dataset

In the previous article, we went through a PyTorch MLP model. In this article, we try to improve the results by creating a Keras MLP model using Tensorflow.

Train and Test Sets

Similarly here, we use StratifiedKFold to keep the same percentage of samples of each target class as the complete set.

Our model here utilizes the accuracy and recall scores.

Conclutions

Comparing the results, we can see that the bACC here is slightly here from our previous model. Moreover, other accuracy parameters showed better results.


Refrences

  1. S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014

  2. S. Moro, R. Laureano and P. Cortez. Using Data Mining for Bank Direct Marketing: An Application of the CRISP-DM Methodology. In P. Novais et al. (Eds.), Proceedings of the European Simulation and Modelling Conference - ESM'2011, pp. 117-121, Guimaraes, Portugal, October, 2011. EUROSIS. [bank.zip]

  3. Scikit-learn Precision-Recall

  4. Mower, Jeffrey P. "PREP-Mt: predictive RNA editor for plant mitochondrial genes." BMC bioinformatics 6.1 (2005): 1-15.

  5. Precision and recall wikipedia page